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Impact of Climate Change on the Spatiotemporal Change in Vegetation Gross Primary Productivity of Marsh Wetlands Across China
Land Degradation & Development ( IF 3.6 ) Pub Date : 2024-11-21 , DOI: 10.1002/ldr.5379 Yanji Wang, Yuan Xin, Jiaqi Zhang, Shouzheng Tong, Ming Jiang, Xianguo Lu, Xiangjin Shen
Land Degradation & Development ( IF 3.6 ) Pub Date : 2024-11-21 , DOI: 10.1002/ldr.5379 Yanji Wang, Yuan Xin, Jiaqi Zhang, Shouzheng Tong, Ming Jiang, Xianguo Lu, Xiangjin Shen
China has the world's third‐largest area of marsh wetlands that plays a critical role in regional and global carbon cycle. Vegetation gross primary productivity (GPP) is a commonly used indicator of carbon sequestration of wetland ecosystems. Although climate change has significantly changed the marsh GPP, the changes in GPP and climatic effects in the marshes of China remian unclear. Using MODIS GPP and climate data during 2001–2020, this study examined the spatiotemporal changes in marsh GPP and its response to climate change in China. The results indicate that the annual averaged GPP over marshes of China increased significantly (4.56 g C/m2 /year), with an average value of 517.39 g C/m2 from 2001 to 2020. Increased annual precipitation significantly enhances the regionally averaged GPP of marshes across China, while mean temperature does not have a significant effect on marsh GPP. Although temperature did not have an obvious effect on the national average GPP, it had a significant effect on the GPP in some marsh regions of China. This study found for the first time the asymmetric influences of daytime and nighttime temperatures on marsh GPP. Specifically, nighttime temperature had a larger positive impact on marsh GPP compared to daytime temperature in China. Increased daytime temperature could decrease annual GPP, while increased nighttime temperature increases the GPP. At a regional scale, the impact of climate change on marsh GPP varies significantly across climate regions. In the Tibetan Plateau marsh region, the increases in annual maximum temperature, annual minimum temperatures, and spring precipitation contribute to the increase in annual marsh GPP. Spatially, the partial correlation results have obvious spatial heterogeneities across China. This study highlights the distinct influences of seasonal climatic change on marsh GPP of different regions and suggests that the asymmetric impacts of day and night temperatures should be fully considered inaccurately simulating and predicting the vegetation productivity in China marsh.
更新日期：2024-11-21
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